Biomarkers Predicting Progression of Human Immunodeficiency Virus-Related Disease
Bibliographic record
Abstract
UNLABELLED: Biomarkers in predicting the progression of HIV infected individuals to a state of HIV disease (AIDS) are studied over more than a decade. Use of surrogate markers in the past for tracking clinical progression of the disease was limited, as little knowledge existed about the disease. The aim of this review was to address various changes in biomarker related studies taking place over the last five years, especially the trend towards use of newer biomarkers and experimentation with novel molecules in a quest for halting HIV disease progression. An open search of PUBMED database was made with search key words such as Biomarkers and AIDS (Acquired Immunodeficiency Syndrome).The following were the inclusion criteria for articles: a) all articles published in English language, b) years of publication between 2002-2008 and c) articles limited to adult population. This yielded a total of 417 articles. The criteria used for further judging these studies considered a) type of research design, b) number of biomarkers studied, c) validity of the biomarkers, d) techniques to assess the biomarkers and the impact of the studies in furthering biomarker research, e) sample size for the studies and f) article title or abstracts having the following key words biomarker or biomarkers and predict progression to AIDS. A total of 27 abstracts were reviewed and 12 studies met the above criteria. These 12 different studies consisted of three reviews, four cohort designs, three cross-sectional designs, one each of an observational, and an in-vitro design. The various biomarkers emerging as a results were primarily a mix of viral, neural, immunological, HLA (human leukocyte antigen) markers along with lymphocyte counts. Although there have been quite a few advancements in biomarker-related studies, majority of the novel biomarkers discovered need to be further evaluated and replicated in bigger, long-term efficacy trials. Efforts should also be made to discover newer genetic markers of disease progression. Biomarker feedback, a new concept, can be utilized in future studies addressing prevention of HIV infection or halting disease progression. KEYWORDS: Biomarkers; Progression; Designs; HIV; AIDS; Validity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".